Real-time Mobile Monitoring of the Dynamic Associations Among Motor Activity, Energy, Mood, and Sleep in Adults With Bipolar Disorder

Greater within- and between-day instability is associated with worse anxiety and depression symptoms

BACKGROUND

Depression and anxiety affect hundreds of millions of people worldwide, and their prevalence increased during the COVID-19 pandemic as social schedules were disrupted. This study explores the associations between anxiety and depression and within- and between-day instability of affective, somatic, and cognitive symptoms during the early pandemic stages.

METHODS

Participants (n = 153, ages 18-77, 72 % female) reported daily levels of affective (anxiety/sadness), somatic (appetite/sleepiness), and cognitive (concentration/energy) symptoms for 14-44 days at five timepoints: 0, 3, 6, 9, and 12 h after awakening. At the end of the study, participants completed validated scales for anxiety (GAD-7) and depression (PHQ-9). Symptom instability was assessed using the Absolute Real Variability (ARV) index. Regression models examined within-day instability (WD-I) and between-day instability (BD-I) with GAD-7 and PHQ-9 scores as outcomes.

RESULTS

Greater instability (both WD-I and BD-I) of affective symptoms correlated with elevated GAD-7 and PHQ-9 scores. For somatic and cognitive symptoms, greater BD-I was associated with higher scores.

LIMITATIONS

The study used retrospective daily data, which could benefit from real-time assessments for improved accuracy.

CONCLUSIONS

This study provides empirical evidence of a connection between greater anxiety and depression severity and increased instability in daily mood and physiological symptoms. The findings underscore the importance of consistent symptom monitoring to understand overall mental health trajectories. Additionally, it highlights the role of daily routines in stabilizing the circadian system, potentially regulating physiological and psychological processes and reducing symptom instability.

Dynamic learning of individual-level suicidal ideation trajectories to enhance mental health care

There has recently been an increase in ongoing patient-report routine outcome monitoring for individuals within clinical care, which has corresponded to increased longitudinal information about an individual. However, many models that are aimed at clinical practice have difficulty fully incorporating this information. This is in part due to the difficulty in dealing with the irregularly time-spaced observations that are common in clinical data. Consequently, we built individual-level continuous-time trajectory models of suicidal ideation for a clinical population (N = 585) with data collected via a digital platform. We demonstrate how such models predict an individual's level and variability of future suicide ideation, with implications for the frequency that individuals may need to be observed. These individual-level predictions provide a more personalised understanding than other predictive methods and have implications for enhanced measurement-based care.

Actigraphic monitoring of sleep and circadian rest-activity rhythm in individuals with major depressive disorder or depressive symptoms: A meta-analysis

BACKGROUND

Disrupted sleep and rest-activity pattern are common clinical features in depressed individuals. This meta-analysis compared sleep and circadian rest-activity rhythms in people with major depressive disorder (MDD) or depressive symptoms and healthy controls.

METHODS

Eligible studies were identified in five databases up to December 2023. The search yielded 53 studies with a total of 11,115 participants, including 4000 depressed participants and 7115 healthy controls.

RESULTS

Pooled meta-analyses demonstrated that depressed individuals have significantly longer sleep latency (SMD = 0.23, 95 % CI: 0.12 to 0.33) and wake time after sleep onset (SMD = 0.37, 95 % CI: 0.22 to 0.52), lower sleep efficiency (SMD = -0.41, 95 % CI: -0.56 to -0.25), more nocturnal awakenings (SMD = 0.58, 95 % CI: 0.29 to 0.88), lower MESOR (SMD = -0.54, 95 % CI: -0.81 to -0.28), amplitude (SMD = -0.33, 95 % CI: -0.57 to -0.09), and interdaily stability (SMD = -0.17, 95 % CI: -0.28 to -0.05), less daytime (SMD = -0.79, 95 % CI: -1.08 to -0.49) and total activities (SMD = -0.89, 95 % CI: -1.28 to -0.50) when compared with healthy controls.

LIMITATIONS

Most of the included studies reported separate sleep and activity parameters instead of 24-hour rest-activity rhythms. The variabilities among actigraphy devices and the types of participants recruited also impede precise comparisons.

CONCLUSIONS

The findings emerging from this study offered a better understanding of sleep and rest-activity rhythm in individuals with MDD or depressive symptoms. Future studies could advocate for deriving objective, distinctive 24-hour rest-activity profiles contributing to the risk of depression.

PROSPERO REGISTRATION NUMBER

CRD42021259780.

The Within-Subject Association of Physical Behavior and Affective Well-Being in Everyday Life: A Systematic Literature Review

BACKGROUND

The interplay of physical activity (PA) with affective well-being (AWB) is highly critical to both health behaviors and health outcomes. Current prominent theories presume AWB to be crucial for PA maintenance, and PA is evidenced to foster mental health. However, thus far, PA-AWB associations have mainly been researched in laboratory settings and with interventional designs, but the everyday life perspective had not been focused on, mostly due to technological limitations. In the course of digitization, the number of studies using device-based methods to research the within-subject association of physical activity and affective well-being (PA-AWB) under ecological valid conditions increased rapidly, but a recent comprehensive systematic review of evidence across populations, age groups, and distinct AWB components remained inconclusive.

OBJECTIVES

Therefore, we aimed to firstly review daily-life studies that assessed intensive longitudinal device-based (e.g., electronic smartphone diaries and accelerometry) and real-time PA-AWB data, secondly to develop and apply a quality assessment tool applicable to those studies, and thirdly to discuss findings and draw implications for research and practice.

METHODS

To this end, the literature was searched in three databases (Web of Science, PubMed, Scopus) up to November 2022. The systematic review followed the PRISMA guidelines and had been pre-registered (PROSPERO id: CRD42021277327). A modified quality assessment tool was developed to illustrate the risk of bias of included studies.

RESULTS

The review of findings showed that, in general, already short PA bouts in everyday life, which clearly differ from structured exercise sessions, are positively associated with AWB. In particular, feelings of energy relate to incidental (non-exercise and unstructured) activity, and PA-AWB associations depend on population characteristics. The quality assessment revealed overall moderate study quality; however, the methods applied were largely heterogeneous between investigations. Overall, the reviewed evidence on PA-AWB associations in everyday life is ambiguous; for example, no clear patterns of directions and strengths of PA-AWB relationships depending on PA and AWB components (such as intensity, emotions, affect, mood) emerged.

CONCLUSIONS

The reviewed evidence can fuel discussions on whether the World Health Organization's notion "every move counts" may be extended to everyday life AWB. Concurrently, the PA-AWB relationship findings endorse prominent theories highlighting the critical role of AWB in everyday PA engagement and maintenance. However, the review also clearly highlights the need to advance and harmonize methodological approaches for more fine-grained investigations on which specific PA/AWB characteristics, contextual factors, and biological determinants underly PA-AWB associations in everyday life. This will enable the field to tackle pressing challenges such as the issue of causality of PA-AWB associations, which will help to shape and refine existing theories to ultimately predict and improve health behavior, thereby feeding into precision medicine approaches.

Protocol for a randomised controlled trial of ketamine versus ketamine and behavioural activation therapy for adults with treatment-resistant depression in the community

INTRODUCTION

Although short-term benefits follow parenteral ketamine for treatment-resistant major depressive disorder (TR-MDD), there are challenges that prevent routine use of ketamine by clinicians. These include acute dissociative effects of parenteral ketamine, high relapse rates following ketamine dosing and the uncertain role of psychotherapy. This randomised controlled trial (RCT) seeks to establish the feasibility of evaluating repeated oral doses of ketamine and behavioural activation therapy (BAT), compared with ketamine treatment alone, for TR-MDD. We also aim to compare relapse rates between treatment arms to determine the effect size of adding BAT to oral ketamine.

METHODS AND ANALYSIS

This is a prospectively registered, two-centre, single-blind RCT. We aim to recruit 60 participants with TR-MDD aged between 18 and 65 years. Participants will be randomised to 8 weeks of oral ketamine and BAT, or 8 weeks of oral ketamine alone. Feasibility will be assessed by tracking attendance for ketamine and BAT, acceptability of treatment measures and retention to the study follow-up protocol. The primary efficacy outcome measure is the Montgomery-Asberg Depression Rating Scale (MADRS) measured weekly during treatment and fortnightly during 12 weeks of follow-up. Other outcome measures will assess the tolerability of ketamine and BAT, cognition and activity (using actigraphy). Participants will be categorised as non-responders, responders, remitters and relapsed during follow-up. MADRS scores will be analysed using a linear mixed model. For a definitive follow-up RCT study to be recommended, the recruitment expectations will be met and efficacy outcomes consistent with a >20% reduction in relapse rates favouring the BAT and ketamine arm will be achieved.

ETHICS AND DISSEMINATION

Ethics approval was granted by the New Zealand Central Health and Disability Ethics Committee (reference: 2023 FULL18176). Study findings will be reported to participants, stakeholder groups, conferences and peer-reviewed publications.

TRIAL REGISTRATION NUMBER

UTN: U1111-1294-9310, ACTRN12623000817640p.

Personalized Machine Learning-Based Prediction of Wellbeing and Empathy in Healthcare Professionals

Healthcare professionals are known to suffer from workplace stress and burnout, which can negatively affect their empathy for patients and quality of care. While existing research has identified factors associated with wellbeing and empathy in healthcare professionals, these efforts are typically focused on the group level, ignoring potentially important individual differences and implications for individualized intervention approaches. In the current study, we implemented N-of-1 personalized machine learning (PML) to predict wellbeing and empathy in healthcare professionals at the individual level, leveraging ecological momentary assessments (EMAs) and smartwatch wearable data. A total of 47 mood and lifestyle feature variables (relating to sleep, diet, exercise, and social connections) were collected daily for up to three months followed by applying eight supervised machine learning (ML) models in a PML pipeline to predict wellbeing and empathy separately. Predictive insight into the model architecture was obtained using Shapley statistics for each of the best-fit personalized models, ranking the importance of each feature for each participant. The best-fit model and top features varied across participants, with anxious mood (13/19) and depressed mood (10/19) being the top predictors in most models. Social connection was a top predictor for wellbeing in 9/12 participants but not for empathy models (1/7). Additionally, empathy and wellbeing were the top predictors of each other in 64% of cases. These findings highlight shared and individual features of wellbeing and empathy in healthcare professionals and suggest that a one-size-fits-all approach to addressing modifiable factors to improve wellbeing and empathy will likely be suboptimal. In the future, such personalized models may serve as actionable insights for healthcare professionals that lead to increased wellness and quality of patient care.

Can we predict a "tsunami"? Symptomatic and syndromal density, mood instability and treatment intensity in people with bipolar disorders under a strict and long lockdown

BACKGROUND

Converging evidence supports the involvement of circadian rhythm disturbances in the course and morbidity of bipolar disorders (BD). During 2020, lockdown measures were introduced worldwide to contain the health crisis caused by the COVID-19 pandemic. As a result, chronobiological rhythms were critically disrupted and illness outcomes were expected to worsen. The current study aimed to explore changes in morbidity among BD patients living under lockdown.

METHODS

Ninety BD outpatients under naturalistic treatment conditions were followed from March to September 2020 using a mood chart technique. Different treatment and illness variables, including mood instability, were assessed and compared with the outcomes obtained during the same 28-week period in 2019.

RESULTS

For most clinical variables, no significant differences were observed between time periods. A slight decrease was found in symptom intensity (from 15.19 ± 20.62 to 10.34 ± 15.79, FDR-adjusted p = 0.04) and in the number of depressive episodes (from 0.39 ± 0.74 to 0.22 ± 0.63, FDR-adjusted p = 0.03), whereas the intensity of pharmacological treatment remained unchanged. Previous illness course predicted mood outcomes during the confinement.

LIMITATIONS

Follow-up periods were relatively short. Further, actigraphy or other methods capable of ensuring significant changes in physical activity were not used.

CONCLUSIONS

In line with other studies, our findings show no worsening in the clinical morbidity of BD patients during lockdown. This conspicuous contrast between our initial predictions and the observed findings highlights the fact that we are still far from being able to provide accurate predictive models for BD.

Causal dynamics of sleep, circadian rhythm, and mood symptoms in patients with major depression and bipolar disorder: insights from longitudinal wearable device data

BACKGROUND

Sleep and circadian rhythm disruptions are common in patients with mood disorders. The intricate relationship between these disruptions and mood has been investigated, but their causal dynamics remain unknown.

METHODS

We analysed data from 139 patients (76 female, mean age = 23.5 ± 3.64 years) with mood disorders who participated in a prospective observational study in South Korea. The patients wore wearable devices to monitor sleep and engaged in smartphone-delivered ecological momentary assessment of mood symptoms. Using a mathematical model, we estimated their daily circadian phase based on sleep data. Subsequently, we obtained daily time series for sleep/circadian phase estimates and mood symptoms spanning >40,000 days. We analysed the causal relationship between the time series using transfer entropy, a non-linear causal inference method.

FINDINGS

The transfer entropy analysis suggested causality from circadian phase disturbance to mood symptoms in both patients with MDD (n = 45) and BD type I (n = 35), as 66.7% and 85.7% of the patients with a large dataset (>600 days) showed causality, but not in patients with BD type II (n = 59). Surprisingly, no causal relationship was suggested between sleep phase disturbances and mood symptoms.

INTERPRETATION

Our findings suggest that in patients with mood disorders, circadian phase disturbances directly precede mood symptoms. This underscores the potential of targeting circadian rhythms in digital medicine, such as sleep or light exposure interventions, to restore circadian phase and thereby manage mood disorders effectively.

FUNDING

Institute for Basic Science, the Human Frontiers Science Program Organization, the National Research Foundation of Korea, and the Ministry of Health & Welfare of South Korea.

Association Between Electronic Diary-Rated Sleep, Mood, Energy, and Stress With Incident Headache in a Community-Based Sample

BACKGROUND AND OBJECTIVES

The aim of this study was to examine the diurnal links between average and changes in average levels of prospectively rated mood, sleep, energy, and stress as predictors of incident headache in a community-based sample.

METHODS

This observational study included structured clinical diagnostic assessment of both headache syndromes and mental disorders and electronic diaries that were administered 4 times per day for 2 weeks yielding a total of 4,974 assessments. The chief outcomes were incident morning (am) and later-day (pm) headaches. Generalized linear mixed-effects models were used to evaluate the average and lagged values of predictors including subjectively rated mood, anxiety, energy, stress, and sleep quality and objectively measured sleep duration and efficiency on incident am and pm headaches.

RESULTS

The sample included 477 participants (61% female), aged 7 through 84 years. After adjusting for demographic and clinical covariates and emotional states, incident am headache was associated with lower average (ß = -0.206*; confidence intervals: -0.397 to -0.017) and a decrease in average sleep quality on the prior day (ß = -0.172*; confidence interval: -0.305, -0.039). Average stress and changes in subjective energy levels on the prior day were associated with incident headaches but with different valence for am (decrease) (ß = -0.145* confidence interval: -0.286, -0.005) and pm (increase) (ß = 0.157*; confidence interval: 0.032, 0.281) headache. Mood and anxiety disorders were not significantly associated with incident headache after controlling for history of a diagnosis of migraine.

DISCUSSION

Both persistent and acute changes in arousal states manifest by subjective sleep quality and energy are salient precursors of incident headaches. Whereas poorer sleep quality and decreased energy on the prior day were associated with incident morning headache, an increase in energy and greater average stress were associated with headache onsets later in the day. Different patterns of predictors of morning and later-day incident headache highlight the role of circadian rhythms in the manifestations of headache. These findings may provide insight into the pathophysiologic processes underlying migraine and inform clinical intervention and prevention. Tracking these systems in real time with mobile technology provides a valuable ancillary tool to traditional clinical assessments.

The sleep-circadian interface: A window into mental disorders

Sleep, circadian rhythms, and mental health are reciprocally interlinked. Disruption to the quality, continuity, and timing of sleep can precipitate or exacerbate psychiatric symptoms in susceptible individuals, while treatments that target sleep-circadian disturbances can alleviate psychopathology. Conversely, psychiatric symptoms can reciprocally exacerbate poor sleep and disrupt clock-controlled processes. Despite progress in elucidating underlying mechanisms, a cohesive approach that integrates the dynamic interactions between psychiatric disorder with both sleep and circadian processes is lacking. This review synthesizes recent evidence for sleep-circadian dysfunction as a transdiagnostic contributor to a range of psychiatric disorders, with an emphasis on biological mechanisms. We highlight observations from adolescent and young adults, who are at greatest risk of developing mental disorders, and for whom early detection and intervention promise the greatest benefit. In particular, we aim to a) integrate sleep and circadian factors implicated in the pathophysiology and treatment of mood, anxiety, and psychosis spectrum disorders, with a transdiagnostic perspective; b) highlight the need to reframe existing knowledge and adopt an integrated approach which recognizes the interaction between sleep and circadian factors; and c) identify important gaps and opportunities for further research.

Directional associations among real-time activity, sleep, mood, and daytime symptoms in major depressive disorder using actigraphy and ecological momentary assessment

Previous research has suggested that individuals with major depressive disorder (MDD) experienced alterations in sleep and activity levels. However, the temporal associations among sleep, activity levels, mood, and daytime symptoms in MDD have not been fully investigated. The present study aimed to fill this gap by utilizing real-time data collected across time points and days. 75 individuals with MDD and 75 age- and gender-matched healthy controls were recruited. Ecological momentary assessments (EMA) were adopted to assess real-time mood status for 7 days, and actigraphy was employed to measure day-to-day sleep-activity patterns. Multilevel modeling analyses were performed. Results revealed a bidirectional association between mood/daytime symptoms and activity levels across EMA intervals. Increased activity levels were predictive of higher alert cognition and positive mood, while an increase in positive mood also predicted more increase in activity levels in depressed individuals. A bidirectional association between sleep and daytime symptoms was also found. Alert cognition was found to be predictive of better sleep in the subsequent night. Contrariwise, higher sleep efficiency predicted improved alert cognition and sleepiness/fatigue the next day. A unidirectional association between sleep and activity levels suggested that higher daytime activity levels predicted a larger increase in sleep efficiency among depressed individuals. This study indicated how mood, activity levels, and sleep were temporally and intricately linked to each other in depressed individuals using actigraphy and EMA. It could pave the way for novel and efficacious treatments for depression that target not just mood but sleep and activity levels.

The definition of treatment resistance in anxiety disorders: a Delphi method-based consensus guideline

Anxiety disorders are very prevalent and often persistent mental disorders, with a considerable rate of treatment resistance which requires regulatory clinical trials of innovative therapeutic interventions. However, an explicit definition of treatment-resistant anxiety disorders (TR-AD) informing such trials is currently lacking. We used a Delphi method-based consensus approach to provide internationally agreed, consistent and clinically useful operational criteria for TR-AD in adults. Following a summary of the current state of knowledge based on international guidelines and an available systematic review, a survey of free-text responses to a 29-item questionnaire on relevant aspects of TR-AD, and an online consensus meeting, a panel of 36 multidisciplinary international experts and stakeholders voted anonymously on written statements in three survey rounds. Consensus was defined as ≥75% of the panel agreeing with a statement. The panel agreed on a set of 14 recommendations for the definition of TR-AD, providing detailed operational criteria for resistance to pharmacological and/or psychotherapeutic treatment, as well as a potential staging model. The panel also evaluated further aspects regarding epidemiological subgroups, comorbidities and biographical factors, the terminology of TR-AD vs. "difficult-to-treat" anxiety disorders, preferences and attitudes of persons with these disorders, and future research directions. This Delphi method-based consensus on operational criteria for TR-AD is expected to serve as a systematic, consistent and practical clinical guideline to aid in designing future mechanistic studies and facilitate clinical trials for regulatory purposes. This effort could ultimately lead to the development of more effective evidence-based stepped-care treatment algorithms for patients with anxiety disorders.

Association between depressive symptoms and dynamic balance among young adults in the community

Background

Detecting and addressing depression symptoms at their outset can reduce the burden on individuals and society; however, it has a limitation in that such evaluations mainly rely on self-reports. Several studies have demonstrated a strong association between motor symptoms and early depression. We aimed to associate body balance measured by the Lower Quarter Y Balance Test (YBT-LQ) with depressive symptoms among young adults in the community, to confirm the current evidence that depression negatively influences body balance.

Research question

Is the YBT-LQ an objective tool for measuring and evaluating young adults' depression risks, as well as assessing whether depression negatively influences body balance?

Methods

Our participants comprised 36 young adults. We assessed their depressive symptoms using the Center for Epidemiological Studies Depression Scale (CES-D) via a Google survey, measured their body balance with the YBT-LQ, and analyzed data with Spearman's rank-order correlation coefficient test, using SPSS version 27.0.

Results

We found that the right leg's anterior, posteromedial, and posterolateral scores- Z = -2.129, p = .033; Z = -2.181, p = .029; and Z = -2.250, p = .024, respectively-and composite scores-Z = 73.00, p = .027 -were significantly lower in the group with risk for clinical depression compared to the normal group. The CES-D total score had a negative association with all YBT-LQ scores, except for the anterior score of the left leg. Among the CES-D sub-factors, somatic and retarded activity showed negative correlations with all the YBT-LQ scores.

Significance

Our findings revealed that depressive symptoms have a negative association with balance, and that the YBT-LQ can be a reliable tool for measuring motor symptoms of depression, specifically among young adults.

Towards Personalised Mood Prediction and Explanation for Depression from Biophysical Data

Digital health applications using Artificial Intelligence (AI) are a promising opportunity to address the widening gap between available resources and mental health needs globally. Increasingly, passively acquired data from wearables are augmented with carefully selected active data from depressed individuals to develop Machine Learning (ML) models of depression based on mood scores. However, most ML models are black box in nature, and hence the outputs are not explainable. Depression is also multimodal, and the reasons for depression may vary significantly between individuals. Explainable and personalised models will thus be beneficial to clinicians to determine the main features that lead to a decline in the mood state of a depressed individual, thus enabling suitable personalised therapy. This is currently lacking. Therefore, this study presents a methodology for developing personalised and accurate Deep Learning (DL)-based predictive mood models for depression, along with novel methods for identifying the key facets that lead to the exacerbation of depressive symptoms. We illustrate our approach by using an existing multimodal dataset containing longitudinal Ecological Momentary Assessments of depression, lifestyle data from wearables and neurocognitive assessments for 14 mild to moderately depressed participants over one month. We develop classification- and regression-based DL models to predict participants' current mood scores-a discrete score given to a participant based on the severity of their depressive symptoms. The models are trained inside eight different evolutionary-algorithm-based optimisation schemes that optimise the model parameters for a maximum predictive performance. A five-fold cross-validation scheme is used to verify the DL model's predictive performance against 10 classical ML-based models, with a model error as low as 6% for some participants. We use the best model from the optimisation process to extract indicators, using SHAP, ALE and Anchors from explainable AI literature to explain why certain predictions are made and how they affect mood. These feature insights can assist health professionals in incorporating personalised interventions into a depressed individual's treatment regimen.

Similarity-based multimodal regression

To better understand complex human phenotypes, large-scale studies have increasingly collected multiple data modalities across domains such as imaging, mobile health, and physical activity. The properties of each data type often differ substantially and require either separate analyses or extensive processing to obtain comparable features for a combined analysis. Multimodal data fusion enables certain analyses on matrix-valued and vector-valued data, but it generally cannot integrate modalities of different dimensions and data structures. For a single data modality, multivariate distance matrix regression provides a distance-based framework for regression accommodating a wide range of data types. However, no distance-based method exists to handle multiple complementary types of data. We propose a novel distance-based regression model, which we refer to as Similarity-based Multimodal Regression (SiMMR), that enables simultaneous regression of multiple modalities through their distance profiles. We demonstrate through simulation, imaging studies, and longitudinal mobile health analyses that our proposed method can detect associations between clinical variables and multimodal data of differing properties and dimensionalities, even with modest sample sizes. We perform experiments to evaluate several different test statistics and provide recommendations for applying our method across a broad range of scenarios.

The added value of a micro-level ecological approach when mapping self-regulatory control processes and externalizing symptoms during adolescence: a systematic review

Deficits in self-regulatory control (SRC) represent a core characteristic of externalizing (EXT) symptoms (e.g., rule-breaking behavior or aggressive behaviors) in adolescents. This review aims to specify the added value of ecologically valid assessments at a micro-level when examining the associations between SRC and EXT symptoms in adolescents. This systematic review was reported according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020. The search strategy addressed the added value of (1) naturalistic assessment for the understanding of the relationship between (2) SRC and (3) EXT symptoms in (4) adolescents. We conducted comprehensive searches in bibliographic databases. An additional search was conducted in Google Scholar and supplementary studies were identified through backward and forward citation tracking. Twenty-four studies (n = 4071 adolescents) met the inclusion criteria. The methods used to assess naturalistic aspects included the experience sampling method (ecological momentary- or ambulatory assessment) and the time-course approach (i.e., real-time assessment of SRC processes referring to situations approximating real-life experience where SRC are to be engaged such as in frustrating situations). Micro-level ecological assessments, when mapping the intra-individual relationships between SRC processes and EXT symptoms over time in adolescents within their natural context (i.e., real world) of expression in real time, added a finer-grained observation alongside with a higher ecological validity. Micro-level approaches may enhance the understanding of the complex interplay between SRC and EXT symptoms in adolescence, especially in interventional studies, allowing for the acquisition of endpoints with a higher relevance for everyday functioning.

Specificity of affective dynamics of bipolar and major depressive disorder

OBJECTIVE

Here, we examine whether the dynamics of the four dimensions of the circumplex model of affect assessed by ecological momentary assessment (EMA) differ among those with bipolar disorder (BD) and major depressive disorder (MDD).

METHODS

Participants aged 11-85 years (n = 362) reported momentary sad, anxious, active, and energetic dimensional states four times per day for 2 weeks. Individuals with lifetime mood disorder subtypes of bipolar-I, bipolar-II, and MDD derived from a semistructured clinical interview were compared to each other and to controls without a lifetime history of psychiatric disorders. Random effects from individual means, inertias, innovation (residual) variances, and cross-lags across the four affective dimensions simultaneously were derived from multivariate dynamic structural equation models.

RESULTS

All mood disorder subtypes were associated with higher levels of sad and anxious mood and lower energy than controls. Those with bipolar-I had lower average activation, and lower energy that was independent of activation, compared to MDD or controls. However, increases in activation were more likely to perpetuate in those with bipolar-I. Bipolar-II was characterized by higher lability of sad and anxious mood compared to bipolar-I and controls but not MDD. Compared to BD and controls, those with MDD exhibited cross-augmentation of sadness and anxiety, and sadness blunted energy.

CONCLUSION

Bipolar-I is more strongly characterized by activation and energy than sad and anxious mood. This distinction has potential implications for both specificity of intervention targets and differential pathways underlying these dynamic affective systems. Confirmation of the longer term stability and generalizability of these findings in future studies is necessary.

Fell on Black Days: Analyzing the Song Lyrics of Chris Cornell for Insight into Depression and Suicide

Chris Cornell was a guitarist, singer, songwriter, and pioneer of grunge music. Cornell struggled with mental illness and addiction and incorporated these themes into his song lyrics. At age 52, Cornell died by suicide in his hotel bathroom following a live performance. This mixed-methods study examines Cornell's song lyrics for references to negative words and themes related to depression and suicide. Two coders independently reviewed lyrical transcripts to identify the primary theme, secondary theme(s), and valence (positive or negative). Sentiment analysis, a natural language processing technique, was used to examine word frequency and valence. Songs (N = 215) were predominantly (79%) negative and contained more negative (N = 3244, 56.1%) than positive (N = 2537, 43.9%) words. Thematic analysis by stage of career shows a narrowing focus on depression, failed relationships, and morbid thoughts. Themes of depressed mood, death, and suicide were common and increased by stage of career. By applying qualitative and quantitative techniques to song lyrics, this study revealed that Cornell's songs reflect a narrative of negativity consistent with someone experiencing depression and thoughts of death and suicide. Like personal notes and poems, song lyrics may reflect symptoms of depression and suicidal thoughts warranting clinical attention.

Bouts of rest and physical activity in C57BL/6J mice

The objective was to exploit the raw data output from a scalable home cage (type IIL IVC) monitoring (HCM) system (DVC®), to characterize pattern of undisrupted rest and physical activity (PA) of C57BL/6J mice. The system's tracking algorithm show that mice in isolation spend 67% of the time in bouts of long rest (≥40s). Sixteen percent is physical activity (PA), split between local movements (6%) and locomotion (10%). Decomposition revealed that a day contains ˜7100 discrete bouts of short and long rest, local and locomotor movements. Mice travel ˜330m per day, mainly during the dark hours, while travelling speed is similar through the light-dark cycle. Locomotor bouts are usually <0.2m and <1% are >1m. Tracking revealed also fits of abnormal behaviour. The starting positions of the bouts showed no preference for the rear over the front of the cage floor, while there was a strong bias for the peripheral (75%) over the central floor area. The composition of bouts has a characteristic circadian pattern, however, intrusive husbandry routines increased bout fragmentation by ˜40%. Extracting electrode activations density (EAD) from the raw data yielded results close to those obtained with the tracking algorithm, with 81% of time in rest (<1 EAD s-1) and 19% in PA. Periods ≥40 s of file when no movement occurs and there is no EAD may correspond to periods of sleep (˜59% of file time). We confirm that EAD correlates closely with movement distance (rs>0.95) and the data agreed in ˜97% of the file time. Thus, albeit EAD being less informative it may serve as a proxy for PA and rest, enabling monitoring group housed mice. The data show that increasing density from one female to two males, and further to three male or female mice had the same effect size on EAD (˜2). In contrast, the EAD deviated significantly from this stepwise increase with 4 mice per cage, suggesting a crowdedness stress inducing sex specific adaptations. We conclude that informative metrics on rest and PA can be automatically extracted from the raw data flow in near-real time (< 1 hrs). As discussed, these metrics relay useful longitudinal information to those that use or care for the animals.

Can daily actigraphic profiles distinguish between different mood states in inpatients with bipolar disorder? An observational study

Background

Criterion A changes for bipolar disorder (BD) in the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition yield new difficulties in diagnosis. Actigraphy has been used to capture the activity features of patients with BD. However, it remains unclear whether long-term actigraphic data could distinguish between different mood states in hospitalized patients with BD.

Methods

In this observational study, 30 hospitalized patients with BD were included. Wrist-worn actigraphs were used to monitor motor activity. The patients were divided into bipolar disorder-depression (BD-D), bipolar disorder-mania (BD-M), and bipolar disorder-mixed state (BD-MS) groups. Motor activity differences were estimated using non-parametric analyses between and within the three groups.

Results

The mean 24 h activity level differed between the groups. In the between-group analysis, the intra-individual fluctuation and minute-to-minute variability in the morning and the mean activity level and minute-to-minute variability in the evening significantly differed between the BD-M and BD-MS groups. In the within-group analysis, the BD-M group showed a disrupted rhythm and reduced activity complexity at night. Both the BD-D and BD-MS groups demonstrated significant differences between several parameters obtained in the morning and evening.

Conclusion

The mean activity levels during the relatively long monitoring period and the intra-day variation within the groups could reflect the differences in motor activity. Sustained activity monitoring may clarify the emotional states and provide information for clinical diagnosis.

Mood instability and activity/energy instability in patients with bipolar disorder according to day-to-day smartphone-based data - An exploratory post hoc study

BACKGROUND

Alterations and instability in mood and activity/energy has been associated with impaired functioning and risk of relapse in bipolar disorder. The present study aimed to investigate whether mood instability and activity/energy instability are associated, and whether these instability measures are associated with stress, quality of life and functioning in patients with bipolar disorder.

METHODS

Data from two studies were combined for exploratory post hoc analyses. Patients with bipolar disorder provided smartphone-based evaluations of mood and activity/energy levels from day-to-day. In addition, information on functioning, perceived stress and quality of life was collected. A total of 316 patients with bipolar disorder were included.

RESULTS

A total of 55,968 observations of patient-reported smartphone-based data collected from day-to-day were available. Regardless of the affective state, there was a statistically significant positive association between mood instability and activity/energy instability in all models (all p-values < 0.0001). There was a statistically significant association between mood and activity/energy instability with patient-reported stress and quality of life (e.g., mood instability and stress: B: 0.098, 95 % CI: 0.085; 0.11, p < 0.0001), and between mood instability and functioning (B: 0.045, 95 % CI: 0.0011; 0.0080, p = 0.010).

LIMITATIONS

Findings should be interpreted with caution since the analyses were exploratory and post hoc by nature.

CONCLUSION

Mood instability and activity/energy instability is suggested to play important roles in the symptomatology of bipolar disorder. This highlight that monitoring and identifying subsyndromal inter-episodic fluctuations in symptoms is clinically recommended. Future studies investigating the effect of treatment on these measures would be interesting.

Shared and distinct abnormalities in sleep-wake patterns and their relationship with the negative symptoms of Schizophrenia Spectrum Disorder patients

Sleep and rest-activity-rhythm (RAR) abnormalities are commonly reported in schizophrenia spectrum disorder (SSD) patients. However, an in-depth characterization of sleep/RAR alterations in SSD, including patients in different treatment settings, and the relationship between these alterations and SSD clinical features (e.g., negative symptoms) is lacking. SSD (N = 137 altogether, N = 79 residential and N = 58 outpatients) and healthy control (HC) subjects (N = 113) were recruited for the DiAPAson project. Participants wore an ActiGraph for seven consecutive days to monitor habitual sleep-RAR patterns. Sleep/rest duration, activity (i.e., M10, calculated on the 10 most active hours), rhythm fragmentation within days (i.e., intra-daily variability, IV; beta, steepness of rest-active changes), and rhythm regularity across days (i.e., inter-daily stability, IS) were computed in each study participant. Negative symptoms were assessed in SSD patients with the Brief Negative Symptom Scale (BNSS). Both SSD groups showed lower M10 and longer sleep/rest duration vs. HC, while only residential patients had more fragmented and irregular rhythms than HC. Compared to outpatients, residential patients had lower M10 and higher beta, IV and IS. Furthermore, residential patients had worse BNSS scores relative to outpatients, and higher IS contributed to between-group differences in BNSS score severity. Altogether, residentials and outpatients SSD had both shared and unique abnormalities in Sleep/RAR measures vs. HC and relative to one another, which also contributed to the patients' negative symptom severity. Future work will help establish whether improving some of these measures may ameliorate the quality of life and clinical symptoms of SSD patients.

Does circadian dysrhythmia drive the switch into high- or low-activation states in bipolar I disorder?

OBJECTIVES

Emerging evidence suggests a role of circadian dysrhythmia in the switch between "activation" states (i.e., objective motor activity and subjective energy) in bipolar I disorder.

METHODS

We examined the evidence with respect to four relevant questions: (1) Are natural or environmental exposures that can disrupt circadian rhythms also related to the switch into high-/low-activation states? (2) Are circadian dysrhythmias (e.g., altered rest/activity rhythms) associated with the switch into activation states in bipolar disorder? (3) Do interventions that affect the circadian system also affect activation states? (4) Are associations between circadian dysrhythmias and activation states influenced by other "third" factors?

RESULTS

Factors that naturally or experimentally alter circadian rhythms (e.g., light exposure) have been shown to relate to activation states; however future studies need to measure circadian rhythms contemporaneously with these natural/experimental factors. Actigraphic measures of circadian dysrhythmias are associated prospectively with the switch into high- or low-activation states, and more studies are needed to establish the most relevant prognostic actigraphy metrics in bipolar disorder. Interventions that can affect the circadian system (e.g., light therapy, lithium) can also reduce the switch into high-/low-activation states. Whether circadian rhythms mediate these clinical effects is an unknown but valuable question. The influence of age, sex, and other confounders on these associations needs to be better characterised.

CONCLUSION

Based on the reviewed evidence, our view is that circadian dysrhythmia is a plausible driver of transitions into high- and low-activation states and deserves prioritisation in research in bipolar disorders.

Exploring digital biomarkers of illness activity in mood episodes: hypotheses generating and model development study

BACKGROUND

Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity alongside physiological alterations that wearables can capture.

OBJECTIVE

We explored whether physiological wearable data could predict: (aim 1) the severity of an acute affective episode at the intra-individual level, (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to the prior predictions, generalization across patients, and associations between affective symptoms and physiological data.

METHODS

We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded with a research-grade wearable (Empatica E4) across three consecutive timepoints (acute, response, and remission of episode). Euthymic patients and healthy controls (HC) were recorded during a single session (∼48 hours). Manic and depressive symptoms were assessed with standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), temperature (TEMP), blood volume pulse (BVP), heart rate (HR), and electrodermal activity (EDA). For data pre-processing, invalid physiological data were removed using a rule-based filter, channels were time-aligned at 1 second time units and then segmented window lengths of 32 seconds, since those parameters showed the best performances. We developed deep learning predictive models, assessed channels' individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales' items normalized mutual information (NMI). We present a novel fully automated method for analysis of physiological data from a research-grade wearable device, including a rule-based filter for invalid data and a viable supervised learning pipeline for time-series analyses.

RESULTS

35 sessions (1,512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 HC (age 39.7±12.6; 31.6% female) were analyzed. (aim 1) The severity of mood episodes was predicted with moderate (62%-85%) accuracies. (aim 2) The polarity of episodes was predicted with moderate (70%) accuracy. The most relevant features for the former tasks were ACC, EDA, and HR. Kendall W showed fair agreement (0.383) in feature importance across classification tasks. Generalization of the former models were of overall low accuracy, with better results for the intra-individual models. "Increased motor activity" was associated with ACC (NMI>0.55), "aggressive behavior" with EDA (NMI=1.0), "insomnia" with ACC (NMI∼0.6), "motor inhibition" with ACC (NMI∼0.75), and "psychic anxiety" with EDA (NMI=0.52).

CONCLUSIONS

Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression respectively. These findings represent a promising pathway towards personalized psychiatry, in which physiological wearable data could allow early identification and intervention of mood episodes.

CLINICALTRIAL

Is insufficient sleep duration a risk indicator for periodontal disease? A systematic review

OBJECTIVES

In this study, we conducted a systematic review and meta-analysis to assess whether people who achieved <7 h of sleep were more likely to develop periodontal disease (PD).

SOURCES

We executed electronic searches in the PubMed, EMBASE and Cochrane Library, as well as a manual search of articles published by leading journals in related fields, for observational studies, published in English from 1 January 1966 to 31 March 2021.which evaluated the relationship between sleep duration and PD. The Agency for Healthcare Research and Quality (AHRQ) quality evaluation scale was used for the cross-sectional studies, and the random effects model was used to summarize the effect sizes in the included studies with a 95% confidence interval (CI).

RESULTS

A total of six cross-sectional studies met the inclusion criteria, totaling 107,777 participants, of which 69,773 had PD. The results of the present indicated that shorter sleep duration (<7 h) is significantly associated with PD (Odd ratio [OR], 1.19; 95% CI, 1.16-1.23; p < 0.001; I² , 0.0%, I² interval, 0%-75%). The strength of the sensitivity analysis and cumulative meta-analysis confirmed the reliability of the results.

CONCLUSION

Although the inclusion of only six studies makes it difficult to explore whether there is a publication bias, we found that insufficient sleep duration was closely related to PD, and we therefore speculated that getting enough sleep may help prevent PD.

A nurse-led mHealth intervention to alleviate depressive symptoms in older adults living alone in the community: A quasi-experimental study

BACKGROUND

The prevalence of geriatric depression has increased worldwide, becoming a major contributor to the burden of health care costs. Geriatric depression is difficult to detect in daily life because of its atypical presentation for each person. Therefore, there is an emerging need to develop personalised mHealth interventions for older adults with depression based on data from an ecological momentary assessment.

OBJECTIVE

To develop and evaluate the effect of a nurse-led mHealth intervention of geriatric depression in older adults living alone.

DESIGN

A quasi-experimental research design was used, and the study followed the transparent reporting of evaluations with a nonrandomised design statement.

SETTING

The nurse-led mHealth intervention was developed and evaluated in a community senior centre in Seoul, Korea.

PARTICIPANTS

Sixty-four older adults living alone with depressive symptoms were recruited between 1 October 2018 and 1 October 2019.

METHODS

Study participants were randomly assigned to the intervention or control groups by drawing lots. In the intervention group, nurses repeatedly assessed older adults' depressive symptoms using an ecological momentary assessment via a mobile tablet. The intervention consisted of weekly sessions, which included (1) standardised mHealth device training, (2) a nurse-led mHealth programme, and (3) art activities. The control group received care as usual. Intra- and inter-group differences were evaluated using paired t-tests and analysis of covariance was used to assess subjective depression symptoms. A linear mixed-model was used to analyse the relationship between groups and momentary scores over time.

RESULTS

The average age of the final sample was 76.2 years (SD = 6.06), 63.6 % (28/44) of whom were female. Compared with the control group (n = 23), the intervention group (n = 21) showed a decreased depression score (t = 4.041, p = .027). There was no statistical difference between the intervention and control groups based on traditional scales and the ecological momentary assessment. However, our data from the ecological momentary assessment captures clear fluctuating patterns across the days during the study, which traditional scales could not measure.

CONCLUSIONS

Most of the older adults successfully participated in a nurse-led mHealth intervention that included multiple components of a non-pharmacological approach to address depression. Mental health nurses should perform critical roles to personalise mHealth activities considering the older adult's autonomy and supportive decision-making, specifically when using high-technological intervention. Future research should maximise the methodological and clinical advantage of an ecological momentary assessment of geriatric depression.

REGISTRATION

Clinical Research Information Service number KCT0005073.

Negative mood states as a correlate of cognitive performance and self-assessment of cognitive performance in bipolar disorder versus schizophrenia

INTRODUCTION

Mood states have been reported to manifest a cross-sectional correlation with self-assessment accuracy across functional domains and psychiatric conditions. Ecological momentary assessment (EMA) provides a strategy to examine the momentary course and correlates of mood states. This study tested the association of moods assessed longitudinally with accuracy of immediate self-assessments of cognitive test performance in participants with schizophrenia and bipolar disorder.

METHODS

240 well-diagnosed participants with schizophrenia and bipolar disorder completed a subset of tests from the MATRICS Consensus Cognitive Battery and an immediate self-assessment of cognitive performance. Differences between actual and self-reported performance were used to index the accuracy of self-assessment. Daily smartphone EMA, 3× per day for 30 days, sampled participants´ momentary moods (sad, happy, relaxed, anxious), aggregated into positive affect and negative affect (NA).

RESULTS

Bipolar participants had better cognitive performance, but both samples had equivalent mis-estimation. Repeated-measures analyses found that NA did not manifest significant variability over time either between or within participants in the two diagnostic groups. Within-group analyses found that higher average NA was associated with greater mis-estimation and poorer cognitive performance in participants with bipolar disorder, but not in those with schizophrenia.

CONCLUSION

Negative moods had a significant association with impairments in self-assessment of cognitive performance in participants with bipolar disorder. Our study did not confirm previous cross-sectional findings of more accurate self-assessment associated with greater NA in schizophrenia. These findings suggest that cross-sectional assessments, particularly self-reports, may lead to different results than aggregated data from longitudinal evaluations.

An examination of bidirectional associations between physical activity and mood symptoms among individuals diagnosed and at risk for bipolar spectrum disorders

OBJECTIVES

Activation, a construct including energy and activity, is a central feature of Bipolar Spectrum Disorders (BSDs). Prior research found motor activity is associated with affect, and this relationship may be stronger for individuals with BSDs. The aims of this study were to investigate bidirectional relationships between physical activity and mood and evaluate whether bipolar risk status moderated potential associations.

METHODS

Young adults at low-risk, high-risk, and diagnosed with BSD participated in a 20-day EMA study in which they wore an actiwatch to measure physical activity and sleep/wake cycles. They also reported depressive and hypo/manic symptoms three times daily. Multilevel linear models were estimated to examine how bipolar risk group moderated bidirectional relationships between physical activity and mood symptoms at within-day and between-day timescales.

RESULTS

Physical activity was significantly associated with subsequent mood symptoms at the within-day level. The relationship between physical activity and depressive symptoms was moderated by BSD risk group. An increase in physical activity resulted in a greater reduction of depressive symptoms for the BSD group compared to the low-risk and high-risk groups.

CONCLUSIONS

Interventions targeting activity like behavioral activation may improve residual inter-episode mood symptoms.

Novel digital methods for gathering intensive time series data in mental health research: scoping review of a rapidly evolving field

Recent technological advances enable the collection of intensive longitudinal data. This scoping review aimed to provide an overview of methods for collecting intensive time series data in mental health research as well as basic principles, current applications, target constructs, and statistical methods for this type of data.In January 2021, the database MEDLINE was searched. Original articles were identified that (1) used active or passive data collection methods to gather intensive longitudinal data in daily life, (2) had a minimum sample size of N ⩾ 100 participants, and (3) included individuals with subclinical or clinical mental health problems.In total, 3799 original articles were identified, of which 174 met inclusion criteria. The most widely used methods were diary techniques (e.g. Experience Sampling Methodology), various types of sensors (e.g. accelerometer), and app usage data. Target constructs included affect, various symptom domains, cognitive processes, sleep, dysfunctional behaviour, physical activity, and social media use. There was strong evidence on feasibility of, and high compliance with, active and passive data collection methods in diverse clinical settings and groups. Study designs, sampling schedules, and measures varied considerably across studies, limiting the generalisability of findings.Gathering intensive longitudinal data has significant potential to advance mental health research. However, more methodological research is required to establish and meet critical quality standards in this rapidly evolving field. Advanced approaches such as digital phenotyping, ecological momentary interventions, and machine-learning methods will be required to efficiently use intensive longitudinal data and deliver personalised digital interventions and services for improving public mental health.

Does awareness of diabetic status increase risk of depressive or anxious symptoms? Findings from the China Multi-Ethnic cohort (CMEC) study

INTRODUCTION

People with diabetes mellitus (DM) have increased risk of depressive symptoms (DS) or anxious symptoms (AS). This study explores whether awareness of DM will contribute to prevalence of DS or AS.

METHODS

The baseline data including 81,717 adults from Southwest China was analyzed. DS and AS were assessed using PHQ-2 and GAD-2. Exposures were defined as 1) having self-reported physician diagnosis of diabetes (self-reported DM), 2) no prior diagnosis of diabetes but meeting diagnostic criteria (newly diagnosed DM), 3) having self-reported physician diagnosis or meeting criteria of non-diabetic diseases (non-diabetic patients), 4) healthy participants. Generalized linear mixed models were used to assess impact of presence and awareness of DM on DS or AS, adjusting for regional and individual related factors.

RESULTS

The prevalence of DS in self-reported DM, newly diagnosed DM, non-diabetic patient and healthy participants was 7.08 %, 4.30 %, 5.37 % and 3.17 %. The prevalence of AS was 7.80 %, 5.77 %, 6.37 % and 3.91 %. After adjusting for related factors, compared with healthy participants, self-reported DM and non-diabetic patients were associated with DS [AOR_{DS, self-reported} = 1.443(1.218,1.710), AOR_{DS, nondiabetic patients} = 1.265(1.143,1.400)], while the association between newly diagnosed DM and DS was not statistically significant. The associations between self-reported DM, newly diagnosed DM, non-diabetic patients and AS were all statistically significant.

LIMITATIONS

DS and AS were assessed through self-report and may suffer recall or information bias.

CONCLUSIONS

The association between awareness of diabetes and DS/AS suggests to pay attention to distinguish between self-reported and newly diagnosed DM and screening for DS and AS in diabetic population.

The relationship between physical activity states and depressive symptoms: Using ambulatory assessment to characterize day-to-day associations among individuals with and without bipolar spectrum disorder

INTRODUCTION

The role of activation in the pathogenesis of bipolar spectrum disorders (BSD) is of growing interest. Physical activity is known to improve mood, but it is unclear whether low activity levels contribute to inter-episode depressive symptoms observed in BSD. This study examined whether sedentary and vigorous activity, as well as the timing of the activity, were differentially associated with next-day depressive symptoms for individuals at low risk for BSD, high-risk for BSD, and diagnosed with BSD.

METHODS

Young adults (n = 111, ages 18-27) from three groups (low BSD risk, high BSD risk, and BSD diagnosis), participated in a 20-day ecological momentary assessment study. Physical activity was measured via wrist actigraphy counts. The percentage of time awake spent in sedentary, light, moderate, and vigorous activity states was calculated, as was the percentage of morning hours and evening hours in each activity state. Multilevel models examined whether the BSD risk group moderated associations between sedentary and vigorous activity and depressive symptoms, which were assessed three times daily.

RESULTS

There were no between-group differences in time spent in each activity state, nor were there main effects of sedentary or vigorous activity on depression. Increased time spent engaging in vigorous activity was associated with a greater reduction in subsequent depressive symptoms for the BSD group. An increase in the evening, but not morning, vigorous activity was significantly associated with a reduction in subsequent depressive symptoms for the BSD group after controlling for chronotype.

CONCLUSIONS

Interventions targeting physical activity may effectively help regulate inter-episode mood disturbances in BSD.

Within-day bidirectional associations between physical activity and affect: A real-time ambulatory study in persons with and without depressive and anxiety disorders

BACKGROUND

Ambulatory assessments offer opportunities to study physical activity level (PAL) and affect at the group and person-level. We examined bidirectional associations between PAL and affect in a 3-h timeframe and evaluated whether associations differ between people with and without current or remitted depression/anxiety.

METHODS

Two-week ecological momentary assessment (EMA) and actigraphy data of 359 participants with current (n = 93), remitted (n = 176), or no (n = 90) Composite International Diagnostic Interview depression/anxiety diagnoses were obtained from the Netherlands Study of Depression and Anxiety. Positive affect (PA) and negative affect (NA) were assessed by EMA 5 times per day. Average PAL between EMA assessments were calculated from actigraphy data.

RESULTS

At the group-level, higher PAL was associated with subsequent higher PA (b = 0.109, p < .001) and lower NA (b = -0.043, p < .001), while higher PA (b = 0.066, p < .001) and lower NA (b = -0.053, p < .001) were associated with subsequent higher PAL. The association between higher PAL and subsequent lower NA was stronger for current depression/anxiety patients than controls (p = .01). At the person-level, analyses revealed heterogeneity in bidirectional associations.

CONCLUSIONS

Higher PAL may improve affect, especially among depression/anxiety patients. As the relationships vary at the person-level, ambulatory assessments may help identify who would benefit from behavioral interventions.

A physically active lifestyle is associated with lower long-term incidence of bipolar disorder in a population-based, large-scale study

Background

Physical activity has been proposed to be beneficial for the symptomatic control of bipolar disorder, but the duration of the effects, sex-specific mechanisms, and impact of exercise intensity are not known.

Method

With an observational study design, we followed skiers and age and sex-matched non-skiers from the general population to investigate if participation in a long-distance cross-country ski race (Vasaloppet) was associated with a lower risk of getting diagnosed with bipolar disorder. Using the Swedish population and patient registries, skiers in Vasaloppet and age and sex-matched non-skiers from the general population were analyzed for any diagnosis of bipolar disorder after participation in the race. Additionally, we used finishing time of the ski race as a proxy for intensity levels to investigate if exercise intensity impacts the risk of bipolar disorder among the physically active skiers.

Results

Previous participation in a long distance ski race (n = 197,685, median age 36 years, 38% women) was associated with a lower incidence of newly diagnosed bipolar compared to an age and sex-matched general population (n = 197,684) during the up to 21 years follow-up (adjusted hazard ratio, HR = 0.48). The finishing time of the race did not significantly impact the risk of bipolar disorder in men. Among women, high performance (measured as the finishing time to complete the race, a proxy for higher exercise dose) was associated with an increased risk of bipolar disorder compared to slower skiing women (HR = 2.07).

Conclusions

Our results confirm that a physically active lifestyle is associated with a lower risk of developing bipolar disorder. Yet, to elucidate the direction of causality in this relationship requires complementary study designs. And the influence of physical performance level on the risk of bipolar disorder warrants further examinations among women.

The clinical characterization of the adult patient with bipolar disorder aimed at personalization of management

Bipolar disorder is heterogeneous in phenomenology, illness trajectory, and response to treatment. Despite evidence for the efficacy of multimodal-ity interventions, the majority of persons affected by this disorder do not achieve and sustain full syndromal recovery. It is eagerly anticipated that combining datasets across various information sources (e.g., hierarchical "multi-omic" measures, electronic health records), analyzed using advanced computational methods (e.g., machine learning), will inform future diagnosis and treatment selection. In the interim, identifying clinically meaningful subgroups of persons with the disorder having differential response to specific treatments at point-of-care is an empirical priority. This paper endeavours to synthesize salient domains in the clinical characterization of the adult patient with bipolar disorder, with the overarching aim to improve health outcomes by informing patient management and treatment considerations. Extant data indicate that characterizing select domains in bipolar disorder provides actionable information and guides shared decision making. For example, it is robustly established that the presence of mixed features - especially during depressive episodes - and of physical and psychiatric comorbidities informs illness trajectory, response to treatment, and suicide risk. In addition, early environmental exposures (e.g., sexual and physical abuse, emotional neglect) are highly associated with more complicated illness presentations, inviting the need for developmentally-oriented and integrated treatment approaches. There have been significant advances in validating subtypes of bipolar disorder (e.g., bipolar I vs. II disorder), particularly in regard to pharmacological interventions. As with other severe mental disorders, social functioning, interpersonal/family relationships and internalized stigma are domains highly relevant to relapse risk, health outcomes, and quality of life. The elevated standardized mortality ratio for completed suicide and suicidal behaviour in bipolar disorder invites the need for characterization of this domain in all patients. The framework of this paper is to describe all the above salient domains, providing a synthesis of extant literature and recommendations for decision support tools and clinical metrics that can be implemented at point-of-care.

Understanding the development of bipolar disorder and borderline personality disorder in young people: a meta-review of systematic reviews

BACKGROUND

There is ongoing debate on the nosological position of bipolar disorder (BD) and borderline personality disorder (BPD). Identifying the unique and shared risks, developmental pathways, and symptoms in emerging BD and BPD could help the field refine aetiological hypotheses and improve the prediction of the onset of these disorders. This study aimed to: (a) systematically synthesise the available evidence from systematic reviews (SRs) and meta-analyses (MAs) concerning environmental, psychosocial, biological, and clinical factors leading to the emergence of BD and BPD; (b) identify the main differences and common features between the two disorders to characterise their complex interplay and, (c) highlight remaining evidence gaps.

METHODS

Data sources were; PubMed, PsychINFO, Embase, Cochrane, CINAHL, Medline, ISI Web of Science. Overlap of included SRs/MAs was assessed using the corrected covered area process. The methodological quality of each included SR and MA was assessed using the AMSTAR.

RESULTS

22 SRs and MAs involving 249 prospective studies met eligibility criteria. Results demonstrated that family history of psychopathology, affective instability, attention deficit hyperactivity disorder, anxiety disorders, depression, sleep disturbances, substance abuse, psychotic symptoms, suicidality, childhood adversity and temperament were common predisposing factors across both disorders. There are also distinct factors specific to emerging BD or BPD.

CONCLUSIONS

Prospective studies are required to increase our understanding of the development of BD and BPD onset and their complex interplay by concurrently examining multiple measures in BD and BPD at-risk populations.

Circadian rhythms and disorders of the timing of sleep

The daily alternation between sleep and wakefulness is one of the most dominant features of our lives and is a manifestation of the intrinsic 24 h rhythmicity underlying almost every aspect of our physiology. Circadian rhythms are generated by networks of molecular oscillators in the brain and peripheral tissues that interact with environmental and behavioural cycles to promote the occurrence of sleep during the environmental night. This alignment is often disturbed, however, by contemporary changes to our living environments, work or social schedules, patterns of light exposure, and biological factors, with consequences not only for sleep timing but also for our physical and mental health. Characterised by undesirable or irregular timing of sleep and wakefulness, in this Series paper we critically examine the existing categories of circadian rhythm sleep-wake disorders and the role of the circadian system in their development. We emphasise how not all disruption to daily rhythms is driven solely by an underlying circadian disturbance, and take a broader, dimensional approach to explore how circadian rhythms and sleep homoeostasis interact with behavioural and environmental factors. Very few high-quality epidemiological and intervention studies exist, and wider recognition and treatment of sleep timing disorders are currently hindered by a scarcity of accessible and objective tools for quantifying sleep and circadian physiology and environmental variables. We therefore assess emerging wearable technology, transcriptomics, and mathematical modelling approaches that promise to accelerate the integration of our knowledge in sleep and circadian science into improved human health.

Effects of adjunctive brexpiprazole on sleep-wake and circadian parameters in youth with depressive disorders: study protocol for a clinical trial

INTRODUCTION

Sleep-wake and circadian disturbance is a key feature of mood disorders with a potential causal role and particular relevance to young people. Brexpiprazole is a second-generation antipsychotic medication with demonstrated efficacy as an adjunct to antidepressant treatment for major depressive disorder (MDD) in adults, with preliminary evidence suggesting greater effectiveness in subgroups of depressed patients with sleep disturbances. This clinical trial aims to evaluate the relationships between changes in sleep-wake and circadian parameters and changes in depressive symptoms following adjunctive brexpiprazole treatment in young adults with MDD and sleep-wake disturbance.

METHODS AND ANALYSIS

This study is designed as a 16 week (8 weeks active treatment, 8 weeks follow-up) mechanistic, open-label, single-arm, phase IV clinical trial and aims to recruit 50 young people aged 18-30 with MDD and sleep-wake cycle disturbance through an early intervention youth mental health clinic in Sydney, Australia. At baseline, participants will undergo multidimensional outcome assessment and subsequently receive 8 weeks of open-label treatment with brexpiprazole as adjunctive to their stable psychotropic medication. Following 4 weeks of treatment, clinical and self-report measures will be repeated. Ambulatory sleep-wake monitoring will be conducted continuously for the duration of treatment. After 8 weeks of treatment, all multidimensional outcome assessments will be repeated. Follow-up visits will be conducted 4 and 8 weeks after trial completion (including sleep-wake, clinical and self-report assessments). Circadian rhythm biomarkers including salivary melatonin, cortisol and core body temperature will be collected during an in-lab assessment. Additionally, metabolic, inflammatory and genetic risk markers will be collected at baseline and after 8 weeks of treatment.

ETHICS AND DISSEMINATION

This trial protocol has been approved by the Human Research Ethics Committee of the Sydney Local Health District (X19-0417 and 2019/ETH12986, Protocol Version 1-3, dated 25 February 2021). The results of this study, in deidentified form, will be disseminated through publication in peer-reviewed journals, scholarly book chapters, presentation at conferences and publication in conference proceedings.

TRIAL REGISTRATION NUMBER

ACTRN12619001456145.

The impact of lithium on circadian rhythms and implications for bipolar disorder pharmacotherapy

Bipolar disorder (BD) is characterized by disrupted circadian rhythms affecting sleep, arousal, and mood. Lithium is among the most effective mood stabilizer treatments for BD, and in addition to improving mood symptoms, stabilizes sleep and activity rhythms in treatment responsive patients. Across a variety of experimental models, lithium has effects on circadian rhythms. However, uncertainty exists as to whether these actions directly pertain to lithium's therapeutic effects. Here, we consider evidence from mechanistic studies in animals and cells and clinical trials in BD patients that identify associations between circadian rhythms and the therapeutic effects of lithium. Most evidence indicates that lithium has effects on cellular circadian rhythms and increases morningness behaviors in BD patients, changes that may contribute to the therapeutic effects of lithium. However, much of this evidence is limited by cross-sectional analyses and/or imprecise proxy markers of clinical outcomes and circadian rhythms in BD patients, while mechanistic studies rely on inference from animals or small numbers of patients . Further study may clarify the essential mechanisms underlying lithium responsive BD, better characterize the longitudinal changes in circadian rhythms in BD patients, and inform the development of therapeutic interventions targeting circadian rhythms.

The acute affective response to physical activity in people with depression: A meta-analysis

BACKGROUND

Little is known about the acute affective response to physical activity in people with depression, which may have implications for acute symptom management and may also be a mechanism that explains the antidepressant effects of physical activity. This study aimed to quantitatively synthesize existing research on the acute affective response to physical activity in people with depression.

METHODS

Five online databases were searched to July 2021 to identify studies that examined pre-post changes in affective states following a bout of moderate-to-vigorous physical activity in people with depression. The affective response to physical activity was synthesized using a random-effects meta-analysis with a robust variance estimator.

RESULTS

A total of 18 studies were included in the meta-analysis. Results showed that people with depression experienced a favourable affective response following an acute bout of physical activity (SMD = 0.585, 95% confidence interval = [0.456, 0.714], 95% prediction interval = [-0.079, 1.249]). Moderator analysis indicated this effect was consistent across different types of affective states, exercise conditions, and participant characteristics. Additionally, results were robust to changes in the study protocol and publication bias.

LIMITATIONS

Only within-person pre-post changes in affective responses were examined. No comparisons were made with control conditions.

CONCLUSION

Acute bouts of physical activity can significantly improve affective states in people with depression. Future research should examine the effect of physical activity on affective states in non-experimental settings and examine whether the affective response to physical activity is a predictor of the long-term antidepressant effects of physical activity interventions.

Perceived stress and depressive symptoms among Chinese college students: A moderated mediation model of biorhythm and ego resilience

Objective

To explore whether biological rhythm disturbance mediates the association between perceived stress and depressive symptoms and to investigate whether ego resilience moderates the mediation model.

Methods

A cross-sectional study was carried out using an online self-report questionnaire distributed to college students from September 2021 to October 2021. Patient Health Questionnaire-9 (PHQ-9), Perceived Stress Severity (PSS-10), the Biological Rhythms Assessment in Neuropsychiatry (BRIAN), and Ego Resilience (ER-96) were used for investigation. SPSS 23 was used for data analyses. The significance of mediation was determined by the PROCESS macro using a bootstrap approach.

Results

Among the participants, 9.2% (N = 1,282) exhibited significant symptoms of depression. Perceived stress was positively associated with depressive symptoms, and biorhythm partially mediated this relationship. The direct and indirect effects were both moderated by ego resilience. Perceived stress had a greater impact on depressive symptoms and biorhythm for college students with lower ego resilience, and the impact of biorhythm on depressive symptoms was also stronger for those with lower ego resilience. Perceived stress had an impact on depressive symptoms directly and indirectly via the mediation of biorhythm.

Conclusion

Schools and educators should guide college students to identify stress correctly and provide effective suggestions to deal with it. Meanwhile, maintaining a stable biorhythm can protect college students from developing depressive symptoms. Students with low resilience should be given more attention and assistance.

Correction of depression-associated circadian rhythm abnormalities is associated with lithium response in bipolar disorder

BACKGROUND

Bipolar disorder (BD) is characterized by episodes of depression and mania and disrupted circadian rhythms. Lithium is an effective therapy for BD, but only 30%-40% of patients are fully responsive. Preclinical models show that lithium alters circadian rhythms. However, it is unknown if the circadian rhythm effects of lithium are essential to its therapeutic properties.

METHODS

In secondary analyses of a multi-center, prospective, trial of lithium for BD, we examined the relationship between circadian rhythms and therapeutic response to lithium. Using standardized instruments, we measured morningness, diurnal changes in mood, sleep, and energy (circadian rhythm disturbances) in a cross-sectional study of 386 BD subjects with varying lithium exposure histories. Next, we tracked symptoms of depression and mania prospectively over 12 weeks in a subset of 88 BD patients initiating treatment with lithium. Total, circadian, and affective mood symptoms were scored separately and analyzed.

RESULTS

Subjects with no prior lithium exposure had the most circadian disruption, while patients stable on lithium monotherapy had the least. Patients who were stable on lithium with another drug or unstable on lithium showed intermediate levels of disruption. Treatment with lithium for 12 weeks yielded significant reductions in total and affective depression symptoms. Lithium responders (Li-Rs) showed improvement in circadian symptoms of depression, but non-responders did not. There was no difference between Li-Rs and nonresponders in affective, circadian, or total symptoms of mania.

CONCLUSIONS

Exposure to lithium is associated with reduced circadian disruption. Lithium response at 12 weeks was selectively associated with the reduction of circadian depressive symptoms. We conclude that stabilization of circadian rhythms may be an important feature of lithium's therapeutic effects.

CLINICAL TRIALS REGISTRY

NCT0127253.

Mobile Health Technology Use and the Acceptability of an mHealth Platform for HIV Prevention Among Men Who Have Sex With Men in Malaysia: Cross-sectional Respondent-Driven Sampling Survey

BACKGROUND

The growth in mobile technology access, utilization, and services holds great promise in facilitating HIV prevention efforts through mobile health (mHealth) interventions in Malaysia. Despite these promising trends, there is a dearth of evidence on the use of mHealth platforms that addresses HIV prevention among Malaysian men who have sex with men.

OBJECTIVE

The goal of this study was to gain insight into (1) access and utilization of communication technology (eg, landline phone, internet, mobile phone), (2) acceptability of mHealth-based interventions for HIV prevention services, and (3) preferences regarding the format and frequency of mHealth interventions among Malaysian men who have sex with men.

METHODS

We conducted a cross-sectional survey with Malaysian men who have sex with men between July 2018 and March 2020. Participants were recruited using respondent-driven sampling in the Greater Kuala Lumpur region of Malaysia. We collected information on demographic characteristics, HIV risk-related behaviors, access to and the frequency of use of communication technology, and acceptability of using mHealth for HIV prevention using a self-administered questionnaire with a 5-point scale (1, never; 2, rarely; 3, sometimes; 4, often; 5, all the time).

RESULTS

A total of 376 men participated in the survey. Almost all respondents owned or had access to a smartphone with internet access (368/376, 97.9%) and accessed the internet daily (373/376, 99.2%), mainly on a smartphone (334/376, 88.8%). Participants on average used smartphones primarily for social networking (mean 4.5, SD 0.8), followed by sending or receiving emails (mean 4.0, SD 1.0), and searching for health-related information (mean 3.5, SD 0.9). There was high acceptance of the use of mHealth for HIV prevention (mean 4.1, SD 1.5), including for receiving HIV prevention information (345/376, 91.8%), receiving medication reminders (336/376, 89.4%), screening and monitoring sexual activity (306/376, 81.4%) or illicit drug use (281/376, 74.7%), and monitoring drug cravings (280/376, 74.5%). Participants overwhelmingly preferred a smartphone app over other modalities (eg, text, phone call, email) for engaging in mHealth HIV prevention tools. Preference for app notifications ranged from 186/336 (53.9%), for receiving HIV prevention information, to 212/336 (69.3%), for screening and monitoring sexual activity. Acceptance of mHealth was higher for those who were university graduates (P=.003), living in a relationship with a partner (P=.04), engaged in sexualized drug use (P=.01), and engaged in receptive anal sex (P=.006).

CONCLUSIONS

Findings from this study provide support for developing and deploying mHealth strategies for HIV prevention using a smartphone app in men who have sex with men-a key population with suboptimal engagement in HIV prevention and treatment.

Comorbidity and Coaggregation of Major Depressive Disorder and Bipolar Disorder and Cannabis Use Disorder in a Controlled Family Study

IMPORTANCE

Cannabis use disorder (CUD) is increasing in the US. Clarification of the potential mechanisms underlying the comorbidity between mood disorders and CUD may help prevent CUD.

OBJECTIVE

To examine co-occurrence and familial aggregation of CUD and mood disorder subtypes.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional, community-based study in the Washington, DC, metropolitan area, semistructured diagnostic interviews and family history reports assessed lifetime DSM-IV disorders in probands and relatives. Familial aggregation and coaggregation of CUD with mood disorders were estimated via mixed-effects models, adjusting for age, sex, recruitment source, and comorbid mood, anxiety, and other substance use disorders. A total of 586 adult probands (186 with bipolar disorder; 55 with CUD) and 698 first-degree relatives (91 with bipolar disorder; 68 with CUD) were recruited from a community screening of the greater Washington, DC, metropolitan area from May 2004 to August 2020. Inclusion criteria were ability to speak English, and availability and consent to contact at least 2 living first-degree relatives.

MAIN OUTCOMES AND MEASURES

Lifetime CUD in first-degree relatives.

RESULTS

Of 586 probands, 395 (67.4%) were female; among 698 relatives, 437 (62.6%) were female. The mean (SD) age was 47.5 (15.2) years for probands and 49.6 (18.0) years for relatives. In the proband group, 82 participants (14.0%) self-identified as African American or Black, 467 (79.7%) as White, and 37 (6.3%) as American Indian or Alaska Native, Asian, more than one race, or another race or ethnicity or declined to respond. In the relative group, 53 participants (7.6%) self-identified as African American or Black, 594 (85.1%) as White, and 51 (7.3%) as American Indian or Alaska Native, Asian, more than one race, or another race or ethnicity or declined to respond. These groups were combined to protect privacy owing to small numbers. CUD in probands (55 [9.4%]) was associated with an increase in CUD in relatives (adjusted odds ratio [aOR], 2.64; 95% CI, 1.20-5.79; P = .02). Bipolar disorder II (BP-II) in probands (72 [12.3%]) was also associated with increased risk of CUD in relatives (aOR, 2.57; 95% CI, 1.06-6.23; P = .04). However, bipolar disorder I (114 [19.5%]) and major depressive disorder (192 [32.8%]) in probands were not significantly associated with CUD in relatives. Among relatives, CUD was associated with BP-II (aOR, 4.50; 95% CI, 1.72-11.77; P = .002), major depressive disorder (aOR, 3.64; 95% CI, 1.78-7.45; P < .001), and mean (SD) age (42.7 [12.8] years with CUD vs 50.3 [18.3] years without CUD; aOR, 0.98; 95% CI, 0.96-1.00; P = .02). Familial coaggregation of BP-II with CUD was attenuated by the inclusion of comorbid anxiety disorders. Further, rates of CUD were highest in relatives with both a familial and individual history of BP-II (no familial or individual history of BP-II: 41 [7.2%]; familial history but no individual history of BP-II: 13 [19.1%]; individual history but no familial history of BP-II: 10 [22.2%]; familial and individual history of BP-II: 4 [28.6%]; Fisher exact test, P < .001). The onset of mood disorder subtypes preceded CUD in probands and relatives in most cases.

CONCLUSIONS AND RELEVANCE

The findings confirmed a familial aggregation of CUD. The increase in risk of CUD among relatives of probands with BP-II suggests that CUD may share a common underlying diathesis with BP-II. Taken together with the temporal precedence of depression and mania with respect to CUD onset, these findings highlight a potential role for BP-II intervention as CUD prevention.

Sleep and circadian informatics data harmonization: a workshop report from the Sleep Research Society and Sleep Research Network

The increasing availability and complexity of sleep and circadian data are equally exciting and challenging. The field is in constant technological development, generating better high-resolution physiological and molecular data than ever before. Yet, the promise of large-scale studies leveraging millions of patients is limited by suboptimal approaches for data sharing and interoperability. As a result, integration of valuable clinical and basic resources is problematic, preventing knowledge discovery and rapid translation of findings into clinical care. To understand the current data landscape in the sleep and circadian domains, the Sleep Research Society (SRS) and the Sleep Research Network (now a task force of the SRS) organized a workshop on informatics and data harmonization, presented at the World Sleep Congress 2019, in Vancouver, Canada. Experts in translational informatics gathered with sleep research experts to discuss opportunities and challenges in defining strategies for data harmonization. The goal of this workshop was to fuel discussion and foster innovative approaches for data integration and development of informatics infrastructure supporting multi-site collaboration. Key recommendations included collecting and storing findable, accessible, interoperable, and reusable data; identifying existing international cohorts and resources supporting research in sleep and circadian biology; and defining the most relevant sleep data elements and associated metadata that could be supported by early integration initiatives. This report introduces foundational concepts with the goal of facilitating engagement between the sleep/circadian and informatics communities and is a call to action for the implementation and adoption of data harmonization strategies in this domain.

Temporal relationships of ecological momentary mood and actigraphy-based sleep measures in bipolar disorder

Sleep disturbances are a key feature of bipolar disorder (BD), and poor sleep has been linked to mood symptoms. Recent use of ecological momentary assessment (EMA) has allowed for nuanced exploration of the sleep-mood link; though, the scale and directionality of this relationship is still unclear. Using EMA, actigraphy, and self-reported sleep measures, this study examines the concurrent and predictive relationships between sleep and mood. Participants with BD (n = 56) wore actigraphy devices for up to 14 days and completed validated scales and daily EMA surveys about mood and sleep quality. Linear mixed models were used to examine overall and time-lagged relationships between sleep and mood variables. EMA mood ratings were correlated with validated rating scales for depression, mania, anxiety, and impulsivity. Poor self-reported sleep quality was associated with worse overall ratings of sadness and anger. Worse self-reported sleep quality was associated with greater sadness the following day. Higher daytime impulsivity was associated with worse sleep quality the following night. Exploratory analyses found relationships between worse and more variable mood (sadness, anger, and impulsivity) with worse and more variable sleep that evening (efficiency, WASO, and sleep onset time). The sample size was modest, fairly homogenous, and included mainly euthymic persons with BD. EMA-based assessments of mood and sleep are correlated with validated scale scores and provide novel insight into intra-individual variability. Further work on the complex two-way interactions between sleep and mood is needed to better understand how to improve outcomes in BD.

A network analysis of rest-activity rhythms in young people with emerging bipolar disorders

AIMS

Actigraphy studies of individuals with bipolar disorders (BD) suggest that illness progression may be associated with a range of progressive disruptions in 24-hour rest-activity rhythms (RAR). However, those longitudinal studies were undertaken in older adults with extended histories or illness and treatment rather than young people with emerging BD. To our knowledge, this is the first study to use network modelling to examine the statistical associations between clinical phenotypes of BD and different subsets of RAR markers.

METHODS

This study of adolescents and young adults (mean age 22 years; 69% female) uses network modelling to examine which self-rated or actigraphic markers of RAR are more strongly associated with full threshold BD (referred to as Stage 2; N = 15) compared with BD-at risk syndromes (subthreshold presentations referred to as Stage 1; N = 25).

RESULTS

Network analysis demonstrated that some RAR are associated with both stage of BD and a family history of BD (such as longer sleep duration and higher levels of daytime impairment). Markers of circadian rhythmicity indicated that regulation of this system is weaker in Stage 2 compared with Stage 1 of BD.

LIMITATIONS

The small subgroup samples may have undermined the ability to detect some associations between phenotypes and RAR.

CONCLUSIONS

Network modelling may offer a useful strategy for visualizing and analysing patterns of association between RAR and clinical phenotypes defined by stage of illness, familial loading or symptom profile. This could prove useful in understanding the underlying pathophysiology of sleep-wake cycle and circadian rhythm disturbances in BD.

Real-world feasibility and acceptability of real-time suicide risk monitoring via smartphones: A 6-month follow-up cohort

Active and passive Ecological Momentary Assessment of suicide risk is crucial for suicide prevention. We aimed to assess the feasibility and acceptability of active and passive smartphone-based EMA in real-world conditions in patients at high risk for suicide. We followed 393 patients at high risk for suicide for six months using two mobile health applications: the MEmind (active) and the eB2 (passive). Retention with active EMA was 79.3% after 1 month and 22.6% after 6 months. Retention with passive EMA was 87.8% after 1 month and 46.6% after 6 months. Satisfaction with the MEmind app, uninstalling the eB2 app and diagnosis of eating disorders were independently associated with stopping active EMA. Satisfaction with the eB2 app and uninstalling the MEmind app were independently associated with stopping passive EMA. Smartphone-based active and passive EMA are feasible and may increase accessibility to mental healthcare.